Questions tagged [reference-request]

Use when requesting examples of research or research papers, books, articles, blog posts or courses. For example, "Is there any published research about X?" or "What are good examples of Y in research?".

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Is there a standardized method to train a reinforcement learning NN by demonstration?

I'm less familiar with reinforcement learning compared to other neural network learning approaches, so I'm unaware of anything exactly like what I want for an approach. I'm wondering if there are any ...
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1 vote
1 answer
22 views

Does LSTM provide any unique value or advantages compared to other algorithms, including "vanilla" RNN?

I have heard a lot of hype around LSTM for all kinds of time-series based applications including NLP. Despite this, I haven't seen many (if any) applications of LSTM where LSTM performs uniquely well ...
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Help finding a recent paper describing how current DL methods are not inspired by biology

I know this is a very long shot, but about a month ago I came across a paper describing how current DL architectures are not inspired by biology, and how the fact that most research only aims to push ...
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Today's Practicality of Bayesian Neural Networks

Just having heard lately about BNNs (wow, ANNs and CNNs are clear; now there's a B? What's that? Ahh, Bayesian ;-)) and quickly getting their main idea and focus, that is, weights not being pure ...
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Deriving the cross entropy loss via maximum-likelihood estimation?

For multi-class classification problems, we use the cross entropy loss, which can be derived from a multinomial distribution via the maximum likelihoos estimation method. I've already tried to derive ...
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31 views

How to combine data measurements with underlying model? [closed]

The problem I am trying to solve is this: Imagine you are in the situation where you want to predict car performance according to some characteristics (horse power, car dimensions, etc...). The data ...
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0 votes
0 answers
30 views

Is Bayesian Reinforcement Learning used as off-policy RL?

Are there any examples where Bayesian Reinforcement Learning is used as off-policy RL? What are the pros and cons of using it for this purpose?
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0 answers
24 views

Are there more optimization methods like GAE for PPO [closed]

I posted about this earlier, but got the suggestion to separate the questions. I'm currently trying to "solve" the OpenAI gym "Humanoid" environment. To improve the training ...
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14 views

How do we call a transformer having N encoders and M decoders and a learnable cross-connectivity between encoders and decoders?

How do we call a transformer having N encoders and M decoders and a learnable cross-connectivity between encoders and decoders? I am interested particularly in the case when M=1, but I imagine that it ...
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1 vote
1 answer
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Current state of the art and datasets for combining NLP and CV?

I was considering a scenario where natural language processing (NLP) and computer vision (CV) are combined, for example in extended reality systems that get as input both natural language and non-...
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  • 121
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18 views

Can machine learning algorithms automatically create formulations of optimizing algorithms?

Suppose we want to create an optimization algorithm which should be able to find an optimum value for non-convex optimization problems. Usually meta-heuristics are used for this purpose. Designing a ...
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2 votes
1 answer
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Does pairing children with their parents cause any harm (in a genetic program)?

If you pair parents with their children (with a cross-over) does this prevent making individuals which are more fit or does this cause other side effects which are harmful to the genetic process? I ...
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3 votes
1 answer
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Is there any variant of perceptron convergence algorithm that ensures uniqueness?

The perceptron convergence algorithm given below ensures the convergence of weights of the perceptron provided enough data points and iterations. Although it ensures convergence by finally getting a ...
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0 answers
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Why does triplet loss allow to learn a ranking whereas contrastive loss only allows to learn similarity?

I am looking at this lecture, which states (link to exact time): What the triplet loss allows us in contrast to the contrastive loss is that we can learn a ranking. So it's not only about similarity, ...
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What are some solid metrics to evaluate/compare the outputs of explainable algorithms?

Consider a learned CNN image classifier and a task that focuses on studying the outputs of explainable algorithms, such as integrated gradients and grad-cam, on the classifier's predictions. I am ...
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1 answer
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Are there any guidelines on how to map the state space to integers in the case tabular RL algorithms?

Let's say that you want to solve a problem with a tabular reinforcement learning algorithm, for example, Q-learning. You can represent the value function $Q(s, a)$ as a $|\mathcal{S}|\times |\mathcal{...
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1 vote
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Is there any research on anger and distrust detection (presence and level of political cynicism)?

The undergrad research project I'm working on would require me to detect presence and level of political cynicism from reddit posts. According to definition political cynicism consists of anger ...
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Is there a multi-task RL algorithm that supports different action spaces for each agent?

I'm currently working on a project in which I need apply multi-task reinforcement learning. Over the same state space, each agent aims to do a separate task, but the action spaces of agents are ...
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2 votes
1 answer
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How to construct a reward function for a "wait and see" problem

I'm working on a problem that I think could probably be represented as a reinforcement learning task, but I'm uncertain about how to design the reward function. The core task is essentially a ...
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0 votes
1 answer
58 views

Is there way to segment an image without labeling/classification, as well as supervised learning?

Is there way to segment an image without labeling/classification, as well as supervised learning? For an illustrative example, if one considers an image with a dog and a cup (we don't particularly ...
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3 votes
2 answers
69 views

How to model a multi-agent reinforcement learning problem where actions of different agents can take different durations?

I am confused on a conceptual scale how I would be able to model a multi-agent reinforcement learning problem when each agent performing an action would take different durations to complete the action....
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0 votes
1 answer
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How can I vectorize fictional single word (not sentence!) for classification?

I am working on fictional single words (names) generator that have to sound like words from a given sample. I have the generator up and running that gives reasonable words 70% of time. I thought of ...
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  • 101
5 votes
1 answer
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Does the term "data augmentation" imply increasing the training dataset?

I have a manuscript that has been reviewed and one of the reviewers commented on my use of the term " data augmentation", saying that it might not be the appropriate term in my case (...
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0 votes
0 answers
32 views

What would be a good cost function based on both saliency-maps and labels?

I have a number of input samples where: every input sample has both a label and a reference-map. This reference-map gives a score to each location of an input sample. The score defines how much this ...
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3 votes
1 answer
85 views

Is it possible to train an AI to bring a picture story in the correct order (correct story flow)?

I want to know if it is possible to train a neural network (or some other kind of an AI) to bring a simple picture story in the correct order, if it is in random order, so that the story has the ...
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0 answers
11 views

Unsupervised methodologies to detect collective anomalies in transaction data

I am researching various methodologies to detect collective anomalies in transactions data. I have seen some supervised approaches, but not the unsupervised ones. Please share any resources or ...
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  • 101
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0 answers
17 views

Which NLP methods use gradient and activation methods?

I am doing a literature review of gradient-based methods for NLP. Yet, apart from linear and logistic regression, I have little knowledge of other methods using the gradient. So, I have no knowledge ...
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0 votes
0 answers
11 views

How to approach in panel data using machine learning?

I have monthly electricity consumption data for the last year of 100k households. So there is a total (100k*12)= 1.2 million data points. I am willing to use this dataset to predict the individual's ...
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0 votes
0 answers
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Given the high resolution signal and the low pass filter (kaiser filter), is there a way to reconstruct the low resolution signal?

When we upsampling a discrete 1d signal by 2x, we first interleave the signal by 0, then pass through a low pass filter. low resolution signal [x1, x2, x3, x4] -> interleave 0 -> [x1, 0, x2, 0, ...
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  • 101
2 votes
1 answer
72 views

How might AI analyze abusive discussion using natural language grammar?

Opening thoughts This does not only apply to SE comments, but the idea in general. This is not a Question for Linguistics.SE; those Questions might come later, after AI analysis. Example Linguistics ...
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1 vote
1 answer
22 views

Are any AI systems available, or in development, for finding and analysing fallacious inference in natural language text?

Poor reasoning, and ignorance in general, is the source of a lot of suffering and evil. Covertly erroneous logic is often used in manipulation. And much of this broken thought is being used directly ...
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0 votes
1 answer
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Where can I find Norvig's version of the pseudocode for the A* search algorithm?

Can anybody point me to a link to Peter Norvig's version of the A* pseudocode. I've googled it interminably but found nothing. It's the version that uses the Unexplored/Frontier/Explored data ...
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18 votes
2 answers
3k views

How do neural networks play chess?

I have been spending a few days trying to wrap my head around how and why neural networks are used to play chess. Although I know very little about how the game of chess works, I can understand the ...
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0 votes
0 answers
32 views

What are the state-of-the-art AI methods to recognize elements on webpages or the purpose of webpage?

I'm curious to know about the capabilities of AI today in 2022. I know that AI has become pretty good at recognizing things like objects in photos. But what about when it comes to elements in HTML? ...
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  • 101
1 vote
0 answers
32 views

What are the best practices of adding noise to game-playing bots?

I write bots that play card games. From time to time, I add noise to their decisions, mainly for two reasons: Reduce predictability: In games with hidden information the optimal play is a mix between ...
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  • 365
0 votes
1 answer
60 views

Avoid unintentional "merging" in cluttered object detection

I have a problem that has bothered me quite some time. With modern methods object detectors can often be accurately trained, even with small to medium sized datasets. However, there is one thing where ...
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0 votes
0 answers
41 views

Example of games in reinforcement learning where no model is available? [duplicate]

I'm reading the Sutton & Barto's book "Reinforcement Learning: An Introduction" (2nd Edition), as the classes I took were a long time ago, and I'm struggling to understand this part (p. ...
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1 vote
0 answers
42 views

Examples of rationalizable AI

The marvelous book Game Changer: AlphaZero's Groundbreaking Chess Strategies and the Promise of AI gave rise to this question. It is - in my opinion - a perfect example of rationalizing a piece of AI ...
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1 vote
0 answers
22 views

References for Nvidia's DLSS

Nvidia's deep learning super-sampling is presented as an application of deep learning techniques to video-rendering in videogames. Question: I'm asking for a technical reference that explains what is ...
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0 votes
0 answers
17 views

Head Pose estimation using Car Interiors depth infromation

I am trying to determine head pose of a driver sitting in a car with the depth interiors of the car known to me. Is there any research work which exploits that information in determining the head pose ...
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0 votes
2 answers
86 views

Are there any works that deal with 2D pose estimation in videos?

Since pose estimation is often a task where spatial-temporal context should be helpful in finding subsequent key points, I thought there should be many papers on it. However, I could not find any work ...
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2 votes
1 answer
81 views

What are the base rules for the symbolic integration implementation?

I want to implement a full symbolic integration. To achieve this. I've learned from Prof. Patrick Winston's AI lecture that Matlab uses 12 safe transformations, like that constant out, sums, etc. 12 ...
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  • 123
1 vote
0 answers
30 views

Is there a paper/article on contextual $\epsilon$-greedy algorithm?

I am reading the paper A Contextual-Bandit Approach to Personalized News Article Recommendation, where it refers to $\epsilon$-greedy (disjoint) algorithm. I suspect, that it is just a version of a K-...
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  • 223
3 votes
1 answer
103 views

What are knowledge graph embeddings?

What are knowledge graph embeddings? How are they useful? Are there any extensive reviews on the subject to know all the details? Note that I am asking this question just to give a quick overview of ...
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0 votes
1 answer
50 views

How do we give recommendations when users create/post content (like in YouTube)?

I've explored tools like amazon personalize, etc. for generating recommendations. It seems like amazon personalize is appropriate when all the content is with the company/a single entity. For example, ...
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0 votes
0 answers
39 views

Algorithms for solving Contextual Bandits Problem with multiples continuous actions

I am currently working on a problem that has 7 continuous actions and instantly gives a reward. I was thinking that there are Contextual-Bandits-Algorithms applicable to this kind of problem, but so ...
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1 vote
1 answer
74 views

How to train an ML model to convert the given lyrics into a song by a particular singer?

I am interested in training a machine algorithm to convert the lyrics I give into a song by a particular singer. My language is non-English (south Indian) The songs are mostly monophonic (very few ...
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  • 15
1 vote
0 answers
10 views

How does the distribution of the parameters change in logistic regression?

I have my own data to train a logistic regression model (for a multi-class classification task), and I want to know how the distribution of weight parameters changes after each update with gradient ...
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2 votes
1 answer
51 views

Is there a mathematical formalism to deal with a missing reward signal?

Typically, a Reinforcement Learning learning problem is formalized as finding an optimal policy for a Markov Decision Process (MDP). In many real-life situations, however, an agent can only get ...
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  • 163
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0 answers
21 views

Is there a way to adapt Particle Swarm Optimization to an incremental/online learning setting?

As stated in the title, is there a way to adapt PSO to an online scenario where new data samples arrive continuously? In more detail: suppose that I have a classifier with several parameters for which ...
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